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Taiwan tech startups present innovative AIoT solutions

Ambrose Huang, Taipei; Willis Ke, DIGITIMES

Wednesday 21 February 2018

AI (artificial intelligence) is deemed as the last integral part of the IoT (Internet of Things) architecture, and the integration of AI and IoT can generate brand new AIoT business opportunities that can be better tapped with creative thinking. As one of the world's tech hubs, Taiwan has witnessed many businesses create innovative and practical business models associated with AIoT applications by taking advantage of the country's robust IT technological prowess.

Among the enterprises, three tech startups presented their latest AIoT solutions at a recent Digitimes-hosted "D Talk" forum: Deep Force, Starwing Technology and AstralNet. They have created new business models with solutions in AI-based image processing, indoor positioning and information security authentication, respectively.

Deep Force uses AI to enhance image values

Deep Force's AI platform can easily help users conduct smart processing of numerous pictures stored in their smartphones for various applications by utilizing deep-learning algorithms, according to company CEO Winston Chen.

Chen said that there are many enterprises engaged in the development of AIoT solutions, but their platforms, devices and chips are usually short of good compatibility. In contrast, he stressed, Deep Force's deep-learning algorithms can not only be compatible with different system equipment and components, but also be easily incorporated into enterprises in the same ecosystems to shorten the time needed for product development and launch through its fast, precision, and high-privacy off-line AI technology able to boost the storage capacity.

Chen continued that the development of both AI and IoT is driven by vertical applications in diverse fields, and therefore no standardized architectures are available. In demanding customized architecture designs, users usually will set the goals for establishing their application systems, and Deep Force will help them select appropriate neural networks in accordance with the goals and optimize the networks to completely fit the application systems before the neural networks and parameters are incorporated into terminal products.

With its AI deep learning technology mainly focused on image processing, Deep Force has rolled out such products as face-unlocking systems and smart albums. The company plans to apply the technology to two-stage authentication, VIP customer services, smart robots, advance driving warning, as well as smart education and sales, which all need AI image processing to boost their service values, according to Chen.

For instance, the authentication by facial recognition can make online trading safer, and operators of physical stores can also use the image analysis of security surveillance systems to judge the personal status of clients so as to provide them with more precise service quality. Chen said that images count high in data-based IoT applications, and AI can help derive more values from the images and stimulate different creativity to generate huge business opportunities.

Starwing offers centimeter-grade indoor positioning system

On another front, hospitals or clinics may need to know patients' locations, and supermarkets may want to know the traffic flow of consumers among store shelves. All these could be addressed with indoor positioning solutions now available in the market, but such solutions usually bear a large deviation of several meters, making precision indoor positioning a difficult job. In this regard, Starwing Technology's centimeter-grade wireless positioning technology can be applied to provide much more precise indoor positioning, according to company president Ian Chen.

Chen said that the current indoor positioning technology is mainly based on triangulation that requires several devices to perform. This, coupled with indoor decorations and furniture that are likely to disturb signals, will lead to a positioning deviation of 2-3 meters. Starwing's Intelligent Indoor Positioning System (IIPS)-Pro adopts the Bluetooh standard and incorporates machine learning algorithms that can automatically adjust deviations to under 30cm to optimize the positioning effect.

In addition, the company has also developed what it calls the world's only 3D vertical positioning technology that can also check the height of the object targeted for positioning, with the deviation also measurable by centimeters.

Chen disclosed that Starwing's positioning tags can well resist electronic interferences, and they can be accurately positioned if they are put inside clothing items. In addition, the company's AI-based data analysis engine can also analyze the positioning data as part of big data, and the company has rolled out AI analysis kits including those for tracing control, hotspot analysis, track prediction and advance security warning, among others.

Precision indoor positioning can be adopted for multiple and practical applications such as museum indoor guide, analysis of consumer traffic flow at shopping malls, detection of patient locations at hospitals, with the accumulated positioning data able to be analyzed through AI algorithms to work out optimal operating models. The company will move to develop modularized application kits for precision indoor positioning, according to Chen.

AstralNet's two-way authentication enhances IoT security

As to information security, it is an important issue for both general networking and IoT applications. As convenience counts high in IoT applications, how to achieve a balance between security and easy operation for IoT has become the most crucial concern for system developers. Ming-yang Chih, co-founder and CTO of AstralNet, opined that in the AI era, IoT information security must be executed in a smarter, easier and faster way.

Chih stressed that AstralNet's two-way SAGE (secure authentication group engine) platform is the exact solution to address the balance issue, as it combines cryptography and AI technology to make IoT designs more secure and easier.

Citing an example to highlight the feature of the platform, Chih pointed out that any modern car comes with a key featuring wireless lock control design, which, however, allows only the key to conduct one-way authentication with the locking system whose password cannot be changed automatically. When the key gets lost, anyone picking the key can easily drive away the car even though the driver gets a new key. But AstralNet's SAGE features a dynamic mutual authentication scheme that can generate a new password whenever a new key is used, thus disabling the lost key.

Chih continued that AstralNet is composed of professionals in the fields of IoT and cryptography, and their combination has created a distinct encryption technology that can perform easier, securer and faster identity authentication for IoT applications. Two-way authentication can be carried out in many ways. For instance, he indicated, a smartphone and a car key can be connected via Bluetooth to undergo fingerprint recognition before being connected to terminal public key infrastructure for two-way authentication.

AstralNet plans to continue expanding the SAGE applications through modularization. Chih said that modularity can accelerate the security designs of IoT systems to facilitate easier and securer device-to-device authentication, stressing that the integration of AI and cryptography can offer smart solutions to eradicate the doubts about security information in IoT applications and promote the popularity of such applications.

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